Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Facundo Bromberg"'
Publikováno v:
AJEA.
El sector residencial representa un elevado porcentaje del consumo de energía global y por ello nacen muchos sistemas de domótica. En el año 1968 surgen los sistemas holónicos, con un gran crecimiento en las últimas décadas. Sin embargo, no exi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::609fc58191c5e86c0f08a90df79a1e70
https://doi.org/10.33414/ajea.5.647.2020
https://doi.org/10.33414/ajea.5.647.2020
In Viticulture, visual inspection of the plant is a necessary task for measuring relevant variables. In many cases, these visual inspections are susceptible to automation through computer vision methods. Bud detection is one such visual task, central
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb09e50751e400e069e0e9f502b3e02c
Publikováno v:
IEEE Internet of Things Journal. 5:4589-4597
Internet of Things (IoT) in agriculture applications have evolved to solve several relevant problems from producers. Here, we describe a component of an IoT-enabled frost prediction system. We follow current approaches for prediction that use machine
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8c63a71125390591ead2e45b294f5140
https://doi.org/10.1109/jiot.2018.2867333
https://doi.org/10.1109/jiot.2018.2867333
Publikováno v:
Computers in Industry. 99:303-312
In viticulture, there are several applications where 3D bud detection and localization in vineyards is a necessary task susceptible to automation: measurement of sunlight exposure, autonomous pruning, bud counting, type-of-bud classification, bud geo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f8f787e5a9896d15d5eb07bafd986c12
https://doi.org/10.1016/j.compind.2018.03.033
https://doi.org/10.1016/j.compind.2018.03.033
Publikováno v:
Computers and Electronics in Agriculture. 135:81-95
In viticulture, there are several applications where bud detection in vineyard images is a necessary task, susceptible of being automated through the use of computer vision methods. A common and effective family of visual detection algorithms are the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ccae5e2c3e5a2c8551beabd12a0be70b
https://doi.org/10.1016/j.compag.2017.01.020
https://doi.org/10.1016/j.compag.2017.01.020
Autor:
Dimitris Margaritis, Facundo Bromberg
We investigate efficient algorithms for learning the structure of a Markov network from data using the independence-based approach. Such algorithms conduct a series of conditional independence tests on data, successively restricting the set of possib
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::297ebe399fed247e814715562e2db9cd
https://doi.org/10.31274/rtd-180813-16791
https://doi.org/10.31274/rtd-180813-16791
Background: Muscle activation level is currently being captured using impractical and expensive devices which make their use in telemedicine settings extremely difficult. To address this issue, a prototype is presented of a non-invasive, easy-to-inst
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a422839808ea261b363a0d38b10ea482
https://www.sciencedirect.com/science/article/pii/S0010482518300416
https://www.sciencedirect.com/science/article/pii/S0010482518300416
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in a wide range of fields. By learning the structure of independences of a domain, more accurate joint probability distributions can be obtained fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2a37e5daf1202b3972655dd63e8d793
http://arxiv.org/abs/1608.02315
http://arxiv.org/abs/1608.02315
Publikováno v:
Expert Systems with Applications. 39:1822-1829
In the past years, several support vector machines (SVM) novelty detection approaches have been applied on the network intrusion detection field. The main advantage of these approaches is that they can characterize normal traffic even when trained wi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7991390c080852444cc1080b6f98354e
https://doi.org/10.1016/j.eswa.2011.08.068
https://doi.org/10.1016/j.eswa.2011.08.068
Autor:
Facundo Bromberg, Dimitris Margaritis
Publikováno v:
Computational Intelligence. 25:367-394
In this paper, we introduce an efficient independence-based algorithm for the induction of the Markov network (MN) structure of a domain from the outcomes of independence test conducted on data. Our algorithm utilizes a particle filter (sequential Mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c822118ba9e66cde1ebe7168479c01d4
https://doi.org/10.1111/j.1467-8640.2009.00347.x
https://doi.org/10.1111/j.1467-8640.2009.00347.x